Uncertainty Quantification for Radar/Inertial Pose Estimation in GNSS-Denied Areas

Jonathan Becker and Mathieu Joerger

Abstract:	In this paper, we first design and analyze a high-fidelity automotive radar radial velocity measurement model for vehicle velocity estimation. We then use this model in a tightly-coupled extended Kalman filter (EKF) algorithm for tight radar/IMU integration (IMU stands for inertial measurement unit). We use both analytical covariance derivation and numerical simulations to quantify the reduction in velocity and positioning error drift of the radar/IMU system as compared to a free-coasting IMU.
Published in:	Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024) September 16 - 20, 2024 Hilton Baltimore Inner Harbor Baltimore, Maryland
Pages:	158 - 179
Cite this article:	Becker, Jonathan, Joerger, Mathieu, "Uncertainty Quantification for Radar/Inertial Pose Estimation in GNSS-Denied Areas," Proceedings of the 37th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2024), Baltimore, Maryland, September 2024, pp. 158-179. https://doi.org/10.33012/2024.19708
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